1. Field of the Invention
The invention generally relates to data processing systems and methods for managing bundles of constructs that may individually fail and that have associated a repetitively updated resource amount usable for counterbalancing a transfer of a failure risk pertaining to the respective bundle of constructs. More particularly, the invention relates to data processing systems and methods for managing futures contracts that are based on a basket of credit default swaps as underlyings.
2. Description of the Related Art
Many techniques exist where a bundle of constructs (which may individually fail) is used. Constructs may be hardware arrangements in computer systems or other automated systems, or may be software routines. It is further well known in the art that even more abstract constructs exist such as a conditional relationship between physical or non-physical entities.
Any such construct may fail, in the sense that the task or function assigned to that construct may not be (completely) fulfilled. For instance, a hardware component may break, a software routine may malfunction or stop performing, or a condition can be rendered void or lead to negative results.
When operating a bundle of constructs that may individually fail, the overall failure risk may depend on the individual failure probabilities. The failure risk may also change with the time. In this case, it is sometimes detrimental that failure events are not exactly predictable. For this reason, the failure risk pertaining to a bundle of constructs may be transferred to an entity that then assumes the overall failure risk. For instance, a hardware controller or a software program may assume the risk that one or more computer hardware or software constructs may fail by stepping into the functions of these constructs in the event of a failure.
To compensate or counterbalance this transfer of a failure risk, the risk assuming entity may receive an extra resource amount. Resources may include, for instance, processor access times, memory capacity, priority over other components in the handling of tasks, etc.
Another field where such techniques can be applied is the valuation of futures contracts that are based on a basket of credit default swaps as underlyings. Credit default swaps are the most commonly traded credit derivatives. A credit default swap is a contract where one party (the “protection seller”) receives a premium from another party (the “protection buyer”) for assuming the credit risk of a specified obligation. In return for this premium, the protection buyer will receive a payment from the protection seller upon the occurrence of a credit event.
However, in all of the above techniques, the compensation is rather difficult to value and the bundles of constructs cannot be easily managed due to the complexity and rapid time variation of the various input parameters. The prior art techniques are therefore cumbersome and often lead to unreliable results.